Classification of the Altered Zone
by the GER Airborne 64 Channel Scanner
T. Takemura, I. Kohno. I. Kaki moto (MSS)
Mitsui Mining & Smelting Co .. LTD.,System Development Office
2-1-1,Nihonbashi-Muromachi,Chuo-ku.Tokyo.l03 Japan
K. Arai, K. Tonoi ke (ERSDAC)
Earth Resources Satel lite Data Analysis Center
No.39 Mori bldg. 2-4-5.Azabudai.Minato-ku.Tokyo.l06 Japan
1.
I NTRODUCT ION
The purpose of this study is to map distribution of calay
minerals
by
using
the
GER
(GeophysIcal
Environmental
Reserch
Corp.) airborne 64 channels imaging spectrometer (AIS) data.
This
study is made over Goldfield, Nevada of USA.
There are many kinds of techniques to analyze AIS data.
The
log residual technique is used for this study, because it is a
method for removing the effects of atmospheric scattering and
absorption. and brightness difference due to slope orientation.
This technique is effecctive in the area with many kinds of clay
minerals and sparse vegetation as Goldfield because small change
in reflectance can be emphasized.
2.
DESCRIPTION OF THE TEST SITE
Goldfield
is
located
in
south
central
Nevada
(Fig.l)
and
prospered in the gold rush the eary years of this century.
Gold
deposits are centerd at 3km NE of the town and are distributed in
N-S direction.
The ore bodies are irregular platy veins in the
hydrothermally
altered
host
rocks.
which
mainly
consist
of
porphyritic rhyodacite.
The altered zone is in a circular shape
with a diameter of 4km (Fig. 1).
3.
THE AIRCRAFT DATA
GER AIS data consist of 63 channels data from visible through
infrared region (Table 1).
Scan parameters are in Table 2.
Each
pixel is rectangular, 20m in azimuth direction (NS). and 15m in
range direction (EW).
The imagery has been used without geometric
correction.
The original data is provided in digital form and is
converted to radiance by the conversion functions supplied by GER.
Data of each channel has different quality. and almost all
data contain line noise.
The data of CH24,......,CH28 is useless for
analysis because of inferior quality.
4. CREATION OF THE LOG RESIDUAL DATA
The flow chart of AIS data analysis by the log residual
technique is shown in Fig.2.
Better results would be expected i f
the line noise was removed. which has no relation with sensor
characteristics.
The
line noise of each line was removed by
equal izeing means of data of each I ine.
After the removal. the
data was converted to radiance, and the log residual data was
calculated.
In visible and near infrared (VNIR) region. data from
CH3 --- CH23 was used for analysis, but data from channell and 2
was ommitted due to low radiance.
In short wave infrared (SWIR)
region. data from CH35"""CH58 was used for analysis due to good
quality.
VII-606
Log residual curves of a pixel in the altered zone are shown
in Fig.3.
The left figure in Fig.3 is in VNIR region. and the
right one is in SWIR region.
A feeble but wide-band absorption by
iron oxide is seen near 850 /1 m in near infrared region.
On the
other hand. in SWIR region. a complex absorption spectrum is seen.
Thus. radiance data in VNIR region was converted to quasireflectance curves by the log residual technique.
In SWIR region.
however, by the log residual technique. noise is excessively
magnified to be interpreted.
The band width is 25.4/1m in VNIR
region, and that is lS.5/1m in SWIR region.
In SWIR region. the
energy that streamed into detectors was not sufficient. and signa\to-noise ratio bacame low.
In order to raise signal-to-noise
ratio in SWIR region. energy which streams into detectors can be
increased by stacking.
To put it in the concrete. the data is
spatially smoothed by a window of 3 x 3 in each channel. and
radiometrically by 3 points running-averages.
Fig.4 shows the log
residual curve of the same pixel as Fig.3 after stacking in SWIR
region.
It can be easely recognized that signal-to-noise ratio is
decreased very much by stacking.
5. EXTRACTION OF IRON OXIDE ZONE USING THE LOG RESIDUAL DATA IN
VNIR REGION
As mentioned above. radiance data in VNIR region was converted
to quasi-reflectance data by the log residual technique.
In log
residual falsecolor image whose R.G,B are assigned to CHI!. CH15,
CHI9 respectively (CHI9 falls in iron oxide absorption band), the
town of Goldfield is yellow. and yellow color suggests that the
reflectance in CH15 is very high as compared with it in CHIl.
That is a result of exaggeration of spectrum charactaristics of
chlorophyl in plants in this area by the log residual.
Blue and
light blue in this image is due to decrease of reflectivity from
CHI5 to CHI9. and this suggests existance of iron oxide.
In a pseudo-color ratio image of the log residual CH15/CH19.
tho areas of red to yel low correspond to high value suggested
existance of iron oxide.
Fig.5 is a line printer image of iron
oxide zone.
S. MAPPING OF CLAY MINERALS USING THE LOG RESIDUAL DATA AFTER
STACKING IN SWIR RESION
Before mapping. new spectral reflectance curves of five clay
minerals such as kaolinite. sericite. montmorillonite. alunite and
cal ci teo were resampl ed from the detai I ed curves. so that the
resampling intervals were adjusted to that of GER AIS data in SWIR
resion.
These resampled spectral reflectance curves were smoothed
by 3 points running-averages. in order to compare with the log
residual data after stacking.
Fig.S shows the running-averaged
spectral reflectance curves after resampling those minerals in
SWIR region.
The vertical axis in Fig.S is set fitting data of
the log residual in the test site. Fig.S suggests that these five
clay minerals should be classified into following three groups;
montmorillonite group including sericite and kaolinite. alunite
group and calcite group.
Clay minerals can automaticai ly be classified by computer.
refering the log residual data after stacking in SWIR region.
In
the clay mapping image with overlaied topographic map. red area
corresponds to montmorillonite group. green area to alunite group.
and blue area to calcite group.
From this image. it is recognized
1... 607
that these groups are complexly distributed.
The alunite groups
seems to be surrounded by montmori lloni te group.
But there are
few areas corresponding to calcite group. Fig.7 is a line printer
image of result of mapping.
Comparing final image and a location map of rock sampl ing
which shows the difference between montmorillonite group and
alunite group. both of them were similar to each other. So that.
the result is sufficient. considering the problem of clay mineral
mixture.
Few areas are classified into calcite group in the final
image and this fact coinsides with what the carbonate rocks as
calcite had not been found in this test site through ground truth.
7. CONCLUSION
In this study. the log residual was calculated from 64
channels AIS data in VNIR region and SWIR region. and analyzed in
order to extract the iron oxide zone and to map clay minerals.
The results of this study are as follows:
CD The iron oxide zone can be extracted by the log residual
analysis in VNIR region.
Extracted iron oxide zone is very
simi lar to the area extracted as the hematic zone by Chebyshev
waveform analysis of GER.
@ The AIS data in SWIR region were scattered because of noise.
This feature is due to insufficient irradiance and also due to
narrow band width of SWIR region.
CID Signal-to-noise ratio of the SWIR region data can be improved
by stacking technique.
After improvement the altered zone is
classified
into montmorillonite group including sericite and
kaolinite. and alunite group.
@ As a final result. the altered zone can be classified into the
following three zones by combination of analyses by VNIR and SWIR
region data;
Montmorillonite zone including sericite and kaolinite. alunite
zone and iron oxide zone.
VII . . 60S
117"'0'
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EXPLANATION:I
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9ase from U.S. Geologico 1 Survey.
Goldfleld,1952~Qnd Mud lake, 1952
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31<ILOMETRES
Fig.l MAP OF THE TEST SITE
VII-609
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___________________ --...II
Alteration contacts by J P. Albers.
H. R. Cornwall, and R. P. Ashley. 1966
N
1
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AIS ORIGINAL DATA
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REMOVING OF LINE NOISES
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CONVERSION TO RADIANCE
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CREATION OF LOG RESIDUAL IMAGES
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DISCUSSION ABOUT LOG RESIDUAL SPECTRUM
VNIR
CREATION OF
FALSECOLOR AND
RATIO IMAGES
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SPECTRAL REFLECTION
CURVES OF
FIVE SAMPLES
SWIR
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SMOOTHING IN
EACH VHANNEL
IMAGES
RESAMPLING OF
SPECTRAL REFLECTION
CURVES
CALCULATION OF
MOVING-AVERAGES
IN EACH SPECTRUM
CALCULATION OF
MOVING-AVERAGES
IN EACH SPECTRUM
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CLASSIFICATION
OF ALTERED ZONE
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LOCATION MAP OF
ROCK SAMPLING
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COMPARISON AND DISCUSSION I
Fig. 2
FLOW CHART OF ANALYSIS OF AIS DATA USING
THE LOG RESIDUAL TECHNIQUE
VII-610
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LOG RESIDUAL CURVES OF A PIXEL IN THE ALTERED ZONE
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CALCITE
VII ... 613
MOVING-AVERAGED SPECTRAL
REFLECTION CURVES AFTER
RESAMPLING OF
MONTMORILLONITE. SERICITE.
KAORINITE. ALUNITE AND
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MONTMORILLONITE ZONE INCLUDING SERICITE AND KAORINITE
@ : ALUNITE ZONE
+
1
CHANNEL
BAND (nm)
BAND WIDTH
Table 1 FORMATION OF AIS DATA
VISIBLE/NEAR INFRARED
2 5 ,.... 31
1
24
420.9 ,....... 984.5 1.020 ~ 1,860
25.4nm
120nm
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Table 2 SCAN PARAMETERS
512 pixels
SWATH WIDTH
SCANNING ANGLE
3 mrad.
20,000 feet
HEIGHT ABOVE THE GROUND
1
INFRARED
32 ,...., 63
1. 978 ,...., 2.5036
16.5nm